Towards Polydisperse Flows with MFIX-Exa

Abstract

In the presence of large size disparities, single-grid neighbor search algorithms lead to inflated neighbor lists that significantly degrade the performance of Lagrangian particle solvers. If Eulerian--Lagrangian (EL) frameworks are to remain performant when simulating realistic systems, improved neighbor detection approaches must be adopted. To this end, we consider the application of a multi-grid neighbor search (MGNS) algorithm in the MFIX-Exa software package, an exascale EL solver built upon the AMReX library. Details regarding the implementation and verification of MGNS are provided along with speedup curves for a bidisperse mixing layer. MGNS is shown to yield up to 15 × speedup on CPU and 6 × speedup on GPU for the problems considered here. The MFIX-Exa software is then validated for a variety of polydisperse flows. Finally, a brief discussion is given for how dynamic MGNS may be completed, with application to spatially varying particle size distributions.